> For the complete documentation index, see [llms.txt](https://docs.ovaledge.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ovaledge.com/release7.2/ai/askedgi.md).

# askEdgi

Data-driven organizations depend on timely, accurate, and context-rich insights to guide strategic and operational decisions. While most AI analysis tools can answer questions about specific datasets, they often operate in isolation from one another and lack awareness of business definitions, governance frameworks, and the broader enterprise data environment. As a result, users face challenges in finding the right data, applying the correct business context, and transforming information into actionable insights.

askEdgi addresses these challenges as a conversational AI assistant embedded within the OvalEdge platform. It understands metadata, governance structures, and organizational knowledge assets, enabling contextual and governance-aware responses.

<figure><img src="https://1813356899-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FhTnkoJQml0pok9awFDhx%2Fuploads%2F0Y6jJPXtRFd3DjRJNqAp%2Fimage.png?alt=media&amp;token=2a943e5f-7f60-43bd-9383-062c8099e915" alt=""><figcaption></figcaption></figure>

The assistant offers capabilities that extend beyond standard AI analysis, including:

* **Metadata Search**: Retrieve tables, columns, glossary terms, reports, and APIs using natural language queries.
* **Knowledge Agent Support**: Guide platform functionality and workflows based on documentation and training resources.
* **Data Analysis**: Explore and analyze datasets directly in the Workspace without requiring SQL or BI tools.
* **AI Enrichment Functions**: Generate calculated columns, perform sentiment and intent analysis, and classify text data.
* **Recipe Creation and Reuse**: Capture analytical workflows in reusable formats for repetition, collaboration, or Marketplace publishing (in Public deployments).

<figure><img src="https://1813356899-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FhTnkoJQml0pok9awFDhx%2Fuploads%2F2IKZl5EQa8tpxaVcSTRu%2Funknown.png?alt=media&amp;token=c36da601-1e48-4bc4-a1d5-28868a92866b" alt=""><figcaption></figcaption></figure>

By bridging AI-powered analysis with platform-native knowledge, askEdgi accelerates discovery, improves data-driven decision-making, and ensures that insights remain aligned with governance policies and business context.

***

Copyright © 2025, OvalEdge LLC, Peachtree Corners, GA USA


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.ovaledge.com/release7.2/ai/askedgi.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.